Modern dental procedures often involve the fabrication of restorations such as crowns, implants, fixed partial dentures, and veneers. Ceramics are often used in such restorations because their optical properties are such that skillfully produced ceramic restorations can closely match the shape, texture, color and translucency of natural teeth.
Producing such realism involves a considerable degree of skill. Tooth color, texture, and translucency vary not only from patient to patient, but also from tooth to tooth in an individual patient and within a single tooth. Teeth vary in shape over a wide range. Information regarding the color and other appearance characteristics of a patient's teeth needs to be accurately determined and unambiguously conveyed to those who will be fabricating the restoration. While molds and other techniques can be used to record and transfer information regarding tooth shape and other geometric characteristics, techniques for determining and conveying color and other appearance characteristics are more problematic.
The most widely used techniques for determining and communicating tooth color information have changed little in the past seventy years. Typically, the process (referred to as “shade matching”) involves visually matching a patient's tooth to one of a number of reference shade samples (shade tabs) within one or more sets of standardized shade guides. The person performing the match, often a dentist, records the identification of the matching shade tab and conveys that information to the dental laboratory where the restoration will be fabricated. The laboratory then uses its own set of the same shade guides to perform visual color evaluations of the restoration throughout the fabrication process.
The visual shade matching process has a number of problems: The initial matching procedure is often long, difficult, and tedious. It is not unusual for the process to take twenty minutes or longer. In most cases, there will be no shade tab that perfectly matches the patient's teeth. Deciding which tab matches most closely (i.e., which mismatches the least) is often problematic. Visual color evaluation of relatively small color differences is always difficult, and the conditions under which dental color evaluations are made are likely to give rise to a number of complicating psychophysical effects such as local chromatic adaptation, local brightness adaptation, and lateral-brightness adaptation. Frequently, the dentist will determine that the patient's teeth are particularly difficult to match. The patient then must go in person to the orthodontics laboratory that will be fabricating the restoration. There, trained laboratory personnel can perform the color match. In many cases, the patient will have to return to the dentist and laboratory two, three, or even more times as the color of the prosthesis is fine tuned by sequential additions of ceramics or other colored materials.
The difficulties associated with dental color matching have led to the development of systems that attempt to replace visual assessments with those determined by various types of spectrophotometric and colorimetric instruments. U.S. Pat. Nos. 6,358,047, 6,305,933, 6,206,691, 6,132,210, and 5,961,324, to Lehmann et al., describe a tooth shade analyzer system in which the preferred embodiment is based on the use of an intra-oral camera providing red, green, and blue (RGB) color values that are subsequently normalized and then used to derive hue, saturation, and intensity (HSI) values using a single set of RGB-to-HSI conversion equations. The derived HSI values are then compared to those derived from corresponding RGB measurements taken of a collection of shade tabs.
U.S. Pat. Nos. 6,190,170 and 6,328,567, to Morris et al., describe a system that uses two or more references to normalize RGB image values from one or more digital cameras. Similarly, U.S. Pat. No. 6,384,917, to Fradkin, describes a system that uses beam splitters and other optical components to obtain RGB image values. Once again, teeth and shade tabs are compared according to their RGB values or to HSI or other values derived from RGB values using a single set of conversion equations. U.S. Patent Application Publication No. US2002/0021439A1, to Priestley et al., also describes a color matching system in which colors are analyzed in terms of RGB values.
The cross-referenced U.S. patent application by Giorgianni and Forsythe, uses multiple subject-specific colorimetric transformations in a dental shade-matching system. Each calorimetric transformation is based on one specific subset of colors (e.g., natural teeth, shade tabs, prosthetic ceramics, etc.). Additionally, colorimetric calibration is provided for each individual camera, each individual set of shade tabs, and each individual intra-oral reference. The system uses a two separate lighting arrangements to minimize or eliminates specular reflections within the area of measurement, and produce images that accurately convey supplemental information such as tooth texture, gloss, and other details. An intra-oral reference is used that has optical properties designed to be well correlated with those of natural teeth. In the system, a shade tab database is built using images of shade tabs photographed with artificial gums and with a background that simulates the human mouth. A standardized set of shade-tab calorimetric values and a corresponding set of computer-generated shade tab images are provided, which can serve as a standard for determining and communicating color specifications. Decision algorithms automatically determine the closest shade-tab match to one or more areas of a specified tooth. The degree of match is indicated in terms of a numerical values, and/or graphical representations, and/or corresponding verbal descriptions. Matching is based on comparisons of regions of interest that are selectable in number and location. Shape and color recognition algorithms simplify and/or fully automate the user task of locating and sizing regions of interest. Optionally, the matching is also determined for any number of other shade tabs in the database, and the results are listed in rank order. The decision algorithm of the system includes parameters that can be adjusted to correspond with various shade-tab selection preferences and objectives. Multiple sets of parameters values, each corresponding to the preferences of a particular user or situation, can be stored and selected for use. An on-screen visual comparison pairs the measured tooth and a selected shade tab. The system provides for visualization of a proposed prosthesis within an image of the patient's mouth. A simulated prosthetic image is created using geometric and other information, from an image of a patient's tooth or from another source, together with colorimetric information derived from the proposed matching shade tab. The system provides a monochrome mode for evaluating lightness, one or more enhanced-chroma modes for evaluating hue, and a mode that simulates the effects of increased viewing distance and squinting. Procedures are provided for measuring a completed prosthesis to either verify that its color meets specifications or, if not, to quantify the color changes required to meet those specifications. A procedure is provided for mapping and compensating for lighting non-uniformity.
A critical feature of a computerized dental color imaging system is locating the tooth of interest. This can be done manually by positioning a small sensor close to a tooth. This approach is cumbersome at handling differences in color and other characteristics within a single tooth. Alternatively, an image can be captured with the tooth of interest centered in the image. This approach is dependent upon the skill of the user. As another alternative, an image can be presented on a computer display and the tooth of interest can be identified by a user input, such as clicking a mouse button when the cursor is over the tooth of interest. This approach tends to be tedious for the user and, thus, prone to errors.
Pixel-based, edge-based, region-based, and model-based segmentation techniques are well known in digital image processing. Each approach has its own limitations. For example, pixel-based segmentation techniques tend to be difficult to apply with complexly shaded and colored objects. Region-growing techniques are subject to critical errors when adjoining objects closely match an object of interest.
It would thus be desirable to provide an improved dental target locating method and apparatus, in which segmentation is automatic and is relatively insensitive to variations in lighting conditions and target color and shape.